Extraction of financial account information from a digital image of a card

ABSTRACT

Capturing information from payment instruments comprises receiving, using one or more computer devices, an image of a back side of a payment instrument, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the payment instrument and the imprinted information is indented into the back side of the payment instrument; extracting sets of characters from the image of the back side of the payment instrument based on the imprinted information indented into the back side of the payment instrument and depicted in the image of the back side of the payment instrument; applying a first character recognition application to process the sets of characters extracted from the image of the back side of the payment instrument; and categorizing each of the sets of characters into one of a plurality of categories relating to information required to conduct a payment transaction.

TECHNICAL FIELD

The present disclosure relates to systems and methods for credit cardprocessing, and, more particularly, to capturing an image of the reverseside of a credit card to gather credit card information.

BACKGROUND

When a consumer makes an online purchase or a purchase using a mobiledevice, they are often forced to enter credit card information into themobile device for payment. Due to the small screen size and keyboardinterface on a mobile device, such entry is generally cumbersome andprone to errors. Users may use many different cards for purchases, suchas credit cards, debit cards, stored value cards, and other cards.Information entry difficulties are multiplied for a merchant attemptingto process mobile payments on mobile devices for multiple transactions.When information from cards is being manually entered, the card mustoften be flipped over to enter additional information from the reverseside of the card, such as a security code or an issuer telephone number.

SUMMARY

One aspect of the example embodiments described herein provides acomputer-implemented method for capturing information from a magneticstripe card. The method comprises receiving, using one or more computerdevices, an image of a back side of a payment instrument, the paymentinstrument comprising information imprinted thereon such that theimprinted information protrudes from a front side of the paymentinstrument and the imprinted information is indented into the back sideof the payment instrument; extracting sets of characters from the imageof the back side of the payment instrument based on the imprintedinformation indented into the back side of the payment instrument anddepicted in the image of the back side of the payment instrument;applying a first character recognition application to process the setsof characters extracted from the image of the back side of the paymentinstrument; and categorizing each of the sets of characters into one ofa plurality of categories relating to information required to conduct apayment transaction.

These and other aspects, objects, features and advantages of the exampleembodiments will become apparent to those having ordinary skill in theart upon consideration of the following detailed description ofillustrated example embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram depicting a payment system using card imagedetection, in accordance with certain example embodiments.

FIG. 2 is a block flow diagram depicting a method for detecting cardinformation from a reverse side image of a card, in accordance withcertain example embodiments.

FIG. 3 is a block diagram depicting a method for detecting cardinformation by comparing results from front and reverse side imagedetection, in accordance with certain example embodiments.

FIG. 4 depicts the front side of a magnetic stripe card, in accordancewith certain example embodiments.

FIG. 5 depicts the back side of a magnetic stripe card, in accordancewith certain example embodiments.

FIG. 6 is a block diagram depicting a computing machine and a module, inaccordance with certain example embodiments.

DETAILED DESCRIPTION OF THE EXAMPLE EMBODIMENTS

Overview

Embodiments herein provide computer-implemented techniques for using animage of the reverse side (back) of a card to recognize the charactersand related information on the card. Throughout the specification, thegeneral term “card” will be used to represent any type of physical cardinstrument, such as a magnetic stripe card. In example embodiments, thedifferent types of card represented by “card” can include credit cards,debit cards, stored value cards, loyalty cards, identification cards, orany other suitable card representing an account of a user or otherinformation thereon.

The user can employ the card when making a transaction, such as apurchase, ticketed entry, loyalty check-in, or other suitabletransaction. The card is typically a plastic card containing the accountinformation and other data on the card. In many card embodiments, thecustomer name, expiration date, and card numbers are physically embossedon the card. The embossed information is visible from both the front andback of the card, although the embossed information is typicallyreversed on the back of the card.

A user may desire to enter the information from the card into a usercomputing device or other computing device, for example, to conduct anonline purchase, to conduct a purchase with a mobile computing device orother computing device, to add the information to a wallet applicationon a computing device, or for any other suitable reason. In an example,the user desires to use a mobile computing device to conduct a purchasetransaction using a digital wallet application module executing on themobile computing device. The digital wallet application module mayrequire an input of the details of a particular user payment account toconduct a with the particular user payment account or to set up theaccount. Due to the small screen size and keyboard interface on a mobiledevice, such entry can be cumbersome and error prone. Additionally, amerchant may need to capture card information to conduct a transactionor for other reasons.

In addition to account identifiers, the front of the card typicallycontains logos of the issuer of the card, pictures chosen by the user orthe issuer, other text describing the type or status of the useraccount, a security code, and other marketing and security elements,such as holograms or badges. The user name, card expiration date, andthe account identifier, such as a credit card number, are typicallyembossed on the front of the card such that the information protrudesfrom the front of the card.

The back, or reverse, of the card contains the reverse of the embossedinformation. That is, the embossing of the information from the front ofthe card is visible on the back of the card, but in a reversed scriptand being depressed into the back of the card. The embossed informationon the back of the card may not be colored as text, but the informationis readable due to the indentation of the information into the back ofthe card. The back of the card may contain other information, such as asecurity code, issuer phone number, and signature of the user. The backof the card may be used for information capturing, and the pictures,holograms, and other elements on the front of the card are not presenton the back of the card to hinder the capturing of the accountinformation from the back of the card. Additionally or alternatively,the user may desire to capture the information on the back of the cardthat is not included on the front of the card, such as the security codeand signature of the user.

The user employs a mobile phone, digital camera, or other user computingdevice to capture an image of the back of the card associated with theaccount that the user desires to input into the mobile computing device.

A card image processing module on the user computing device receives theimage of the back of the card. The card image processing moduleprocesses the image to remove perspective distortion. For example, theimage may not have been captured from the preferred angle, or the cardin the image may not fit the required frame for the image. The cardimage processing module can alter or resize the image to fit anyrequired parameters for processing in the manner in which the imageprocessing module is configured to process images. In an example, thecard image processing module can detect the corners or edges of the cardin the image and then map the corners or edges to a rectangle of thecorrect ratios for a credit card. The card image processing module canperform any other required image adjustments to provide a clear anduseful image suitable for processing to obtain information includedtherein.

The card image processing module detects the reversed embossedcharacters on the back of the card. For example, the card imageprocessing module can detect the credit card number, name, expirationdate, and other embossed information from the back of card. Thedetection can leverage known specifications for where characters areembossed within the space of the card, by analyzing specific locationson the card for the corresponding information included in each specificlocation. Additionally, the card image processing module can search theimage of the card for information that is not located in an expectedlocation. The card image processing module can employ characterrecognition algorithms or related techniques to identify a set ofcharacters from the information identified on the card.

Once embossed characters are located within the image of the back of thecard, they can be reversed, or mirrored, for normal recognition. Thatis, as the embossed images on the back of the card are reversed, thecard image processing module can process the characters to provide amirror image of the characters to allow a character recognitionalgorithm to interpret the characters. After processing, the embossedset of characters appears “debossed” and reversed from the image.Alternatively, a reverse character recognition algorithm may be usedthat is capable of interpreting reversed characters.

The card image processing module can additionally or alternativelydetect additional printed information from the back of the card that isnot embossed or reversed. For example, the security code, signature,issuer name, address, and phone number, and other information of theissuing institution are generally not embossed and are generally locatedon the back of a card.

After processing the information from the image to obtain analpha-numeric character set for the information from the image, the cardimage processing module can verify uncertain detection with the user.For example, the user may be queried to verify the processed informationvia a user interface provided by the card image processing module or theuser computing device. The user may be prompted to verify the cardinformation as a default for some or all of the information.Alternatively, the user may only be required to verify information ifthe detection algorithms have a low confidence in the accuracy of theprocessed information.

The card image processing module can categorize the information obtainedfrom the card. For example, the card image processing module candetermine that a set of characters from the card relates to the accountnumber, the user name, the expiration data, and other suitableinformation. The set of characters can be stored in the card imageprocessing module with a designation associating the series ofcharacters with the appropriate category. For example, a series of 16numbers would be associated with an account identifier. A four digitseries with a “/” in the middle would be associated with an expirationdate.

The card image processing module can provide detected card informationfor further processing. In certain embodiments, the information may becommunicated to a payment processing system or other computing system toprocess a payment or other operation associated with the card. Forexample, the card image processing module can communicate the cardinformation to a digital wallet application module executing on the usercomputing device or otherwise associated with the user of the card foruse in a transaction with a merchant or other entity. In anotherexample, the user computing device can use the card information topopulate a payment form or other online transaction form to conduct atransaction. In another example, a merchant can use the card informationto populate a transaction page on a point of sale terminal or othertransaction user interface. The card information can be employed for anyother suitable purpose.

In an example embodiment, correlation between images of the front andback of the card may help improve the accuracy of reading the card. Animage of the front of the card may be harder to read because ofbackground images, the embossing, and other information provided on thefront of the card. The back of the card often overlaps with customerservice information, the signature, or other images or information.Thus, errors may occur when extracting the characters and other userinformation from an image of the card.

Since both the front and the back of the card contain some of the sameuser information, for example, the embossed information, the card imageprocessing module can compare information from the front of the cardwith information from the back of the card and note similarities anddifferences. Information from the front of the card that matches theinformation from the back of the card can be expected to be moreaccurate. If the information from the front of the card does not matchthe same information on the back of the card, then the card imageprocessing module may require user input to select or input the correctinformation.

To compare the information from the images of the front and back of thecard, the card image processing module can perform the method describedpreviously to obtain the information from the back of the card and canperform a similar method to obtain the information from the front of thecard. After determining the category of each series of characters fromthe images of the front and back of the card, the card image processingmodule can compare the information from the front of the card with theinformation from the back of the card.

For example, the card image processing module can compare a series ofcharacters from the back associated with the user name to the series ofcharacters from the front associated with the user name. The card imageprocessing module can use the comparison to determine a confidence scorefor the accuracy of the user name. If the comparison produces an exactmatch, then the confidence score for the user name would be high. If aconflict exists between the two, then the confidence score for the username would be lower. The relative confidence score can depend on anumber of conflicts between the information from the front and backsides of the card. If the confidence score is below a configurablethreshold, the card image processing module may request an input fromthe user to verify the correct information. For example, the card imageprocessing module may provide the results extracted from the front ofthe card and the results extracted from the back of the card and allowthe user to select the correct information or input alternateinformation.

In an example embodiment, the card image processing module can applyindependent character recognition applications to the characters on thefront and back of the card. For example, the card image processingmodule can host two or more character recognition applications and applyone character recognition application to the front of the card and adifferent character recognition application to the back of the card.After determining the category of each series of characters, the cardimage processing module can compare the information from the front ofthe card with the information from the back of the card to improve theaccuracy of the information. The agreement of different characterrecognizer processing applications on the characters on the front andback of the card can provide a greater degree of confidence in theextracted information.

In another example embodiment, the card image processing module canextract features from corresponding locations on the front and back ofthe card, and feed the combined features into a single classifier. Thecard image processing module can extract the embossed characters fromthe same area of the card on the front and the back. For example, thecard image processing module can extract the account number from thefront of the card and combine the characters with the charactersextracted from the same, although reversed, location on the back of thecard.

The card image processing module can reverse one of the sets ofcharacters and process the two sets of characters together to achieve amore accurate set of characters. The card image processing module canapply a character recognition application to the characters to identifythe set of characters and categorize the information.

In another example embodiment, the card image processing module cansearch for and identify correlations between pixels on the front andback of the card, and extract pixels for which there are strongcorrelations. The card image processing module can process digitalimages of the front and back of the card and compare the individualpixels searching for correlations and differences. The pixels with highcorrelations are likely to be corresponding parts of characters ratherthan of the backgrounds. The correlated pixels can allow a greater levelof accuracy when identifying and recognizing characters.

In another example embodiment, the card image processing module can usemore than one source to extract additional information. The card imageprocessing module can process multiple images of the front, the back, orboth. For example, the user can provide multiple images captured fromdifferent angles to allow the card image processing module to betterfilter shadows, scratches, or other obstructions. Additionally oralternatively, the user can provide a video moving across the card suchthat many angles can provide more information to the card imageprocessing module for processing.

Although described herein as executing on the user computing device, thecard image processing module can execute on any suitable computingdevice. For example, the card image processing module can execute on apayment processing system, a merchant point of sale system, a digitalwallet account management system, or other suitable computing system. Inthese embodiments, the captured images of the front and back of the cardare communicated from the image capture device to the processingcomputing system for processing of the image information.

Example System Architectures

Turning now to the drawings, in which like numerals represent like (butnot necessarily identical) elements throughout the figures, exampleembodiments are described in detail.

FIG. 1 is a block diagram depicting a system for capturing an image ofthe front and/or reverse side of a credit card to gather credit cardinformation, in accordance with certain example embodiments. As depictedin FIG. 1, the system 100 includes network devices 110 and 140 that areconfigured to communicate with one another via one or more networks 105.

Each network 105 includes a wired or wireless telecommunication means bywhich network devices (including devices 110 and 140) can exchange data.For example, each network 105 can include a local area network (“LAN”),a wide area network (“WAN”), an intranet, an Internet, a mobiletelephone network, or any combination thereof. Throughout the discussionof example embodiments, it should be understood that the terms “data”and “information” are used interchangeably herein to refer to text,images, audio, video, or any other form of information that can exist ina computer-based environment.

Each network device 110 and 140 includes a device having a communicationmodule capable of transmitting and receiving data over the network 105.For example, each network device 110 and 140 can include a server,desktop computer, laptop computer, tablet computer, a television withone or more processors embedded therein and/or coupled thereto, smartphone, handheld computer, personal digital assistant (“PDA”), or anyother wired or wireless, processor-driven device. In the exampleembodiment depicted in FIG. 1, the network devices 110 and 140 areoperated by end-users and payment system operators, respectively.

The user computing device 110, payment processing system 140, and anyother computing machines associated with the technology presented hereinmay be any type of computing machine such as, but not limited to, thosediscussed in more detail with respect to FIG. 5. Furthermore, anymodules associated with any of these computing machines such as the cardimage processing module 115 or any other modules (scripts, web content,software, firmware, or hardware) associated with the technologypresented herein may by any of the modules discussed in more detail withrespect to FIG. 5. The computing machines discussed herein maycommunicate with one another as well as other computer machines orcommunication systems over one or more networks such as network 105. Thenetwork 105 may include any type of data or communications networkincluding any of the network technology discussed with respect to FIG.5.

The user 101 can use the communication application 112, which may be,for example, a web browser application or a stand-alone application, toview, download, upload, or otherwise access documents or web pages via adistributed network 105. The network 105 includes a wired or wirelesstelecommunication system or device by which network devices (includingdevices 110 and 140) can exchange data. For example, the network 105 caninclude a local area network (“LAN”), a wide area network (“WAN”), anintranet, an Internet, storage area network (SAN), personal area network(PAN), a metropolitan area network (MAN), a wireless local area network(WLAN), a virtual private network (VPN), a cellular or other mobilecommunication network, Bluetooth, NFC, or any combination thereof or anyother appropriate architecture or system that facilitates thecommunication of signals, data, and/or messages.

The communication application 112 can interact with web servers or othercomputing devices connected to the network 105, including the web server144 of the payment system 140.

The user network device 110 may include a digital wallet applicationmodule 111. The digital wallet application module 111 may encompass anyapplication, hardware, software, or process the user computing device110 may employ to assist the user 101 in completing a purchase. Thedigital wallet application module 111 can interact with thecommunication application 112 or can be embodied as a companionapplication of the communication application 112. As a companionapplication, the digital wallet application module 111 executes withinthe communication application 112. That is, the digital walletapplication module 111 may be an application program embedded in thecommunication application 112.

The user computing device 110 can include a card image processing module115. The card image processing module 115 can interact with thecommunication application 112 or be embodied as a companion applicationof the communication application 112 and execute within thecommunication application 112. The card image processing module 115 mayfurther be embodied as a companion application of the digital walletapplication module 111 and execute within the digital wallet applicationmodule 111. The card image processing module 115 may employ a softwareinterface for configuration that may open in the digital walletapplication module 111 or may open in the web browser application 112.Alternatively, the card image processing module 115 may be execute onthe user computing device 110 independent of the digital walletapplication module 111 and the communication application 112. The cardimage processing module 115 can be operable to process an image ofpayment instrument card or other image of a payment instrument and toextract useful information from the image to facilitate a transaction.

Any functions of the card image processing module 115 can be performedby the digital wallet application 111 or other module or application onthe user computing device or the payment processing system 140.

The user computing device 110 also includes a data storage unit 113accessible by the digital wallet application module 111, the proxy cardapplication 115, and the communication application 112. The example datastorage unit 113 can include one or more tangible computer-readablestorage devices. The data storage unit 113 can be stored on the usercomputing device 110 or can be logically coupled to the user computingdevice 110. For example, the data storage unit 113 can include on-boardflash memory and/or one or more removable memory cards or removableflash memory.

The user 101 may use the user computing device 110 or other networkdevice to register the card image processing module 115 and/or accessthe payment system account of the user 101. The user computing device110 may comprise appropriate technology that includes or is coupled to aweb server.

Credit cards, debit cards or other payment instrument can be representedas a magnetic stripe card 120. The magnetic stripe card 120 can be usedto conduct transactions with payment accounts such as debit cards,credit cards, gift cards/stored value cards, loyalty cards/reward cards,peer-to-peer payment accounts, coupons, prepaid or other offers, andother accounts used to make a purchase or redeem value added services.

The magnetic stripe card 120 can be a physical payment card comprising amagnetic stripe or other machine-readable portion comprising the user'sproxy card account identifier and other payment information. In thiscase, the user scans or swipes the magnetic stripe card 120 at amerchant POS terminal to communicate the magnetic stripe card accountidentifier and other transaction data to the POS terminal. Additionallyor alternatively, the magnetic stripe card 120 can be represented as anyother suitable payment instrument, such as an RFID device or asmartcard.

The payment processing system 140 includes a data storage unit 147accessible by the web server 144. The example data storage unit 147 caninclude one or more tangible computer-readable storage devices. Thepayment processing system 140 is operable to conduct contactlesspayments between a user 101. The payment processing system 140 isfurther operable to maintain a database to store transactions of amerchant system and the user 101, and other suitable functions.

The user 101 can use a web server 144 on the payment processing system140 to view, register, download, upload, or otherwise access the paymentprocessing system 140 via a website (not illustrated) and acommunication network 105). The user 101 associates one or moreregistered financial card accounts, including bank account debit cards,credit cards, gift cards, loyalty cards, coupons, offers, prepaidoffers, store rewards cards, or other type of financial account that canbe used to make a purchase or redeem value-added services with a paymentaccount of the user 101. The payment processing system 140 also mayfunction as the issuer for the associated financial account. The user's101 registration information is saved in the payment processing system's140 data storage unit 147 and is accessible the by web server 144.

FIG. 4 depicts the front side of a magnetic stripe card 120, inaccordance with certain example embodiments. In the example, themagnetic stripe card is a credit card issued by Bank A. The magneticstripe card 120 could be any other payment instrument, such as a debitcard, a credit card, a gift card/stored value card, a loyaltycard/reward card, a peer-to-peer payment account, a coupon, a prepaid orother offer, and other accounts used to make a purchase or redeem valueadded services.

In the example, the magnetic stripe card 120 displays a logo 405 orother text or diagram identifying the issuer of the credit card, thecard network the card employs, or other identifiers of the card 120. Themagnetic stripe card 120 has a number 415 identifying the account numberof the user 101. The account number 415 can be any combination ofcharacters, such as numbers or letters, which can identify the accountof the user 101 when the magnetic stripe card 120 is used in atransaction. The magnetic stripe card 120 displays the name 410 of theuser 101. The magnetic stripe card 120 displays an expiration date 420of the magnetic stripe card 120. The expiration date 420 is establishedby the payment processing system 140 or other issuer of the magneticstripe card 120. Typically, the account number 415, the user name 410,and the expiration date 420 are embossed on the card or otherwiserendered in raised letters and numbers.

FIG. 5 depicts the back side of a magnetic stripe card 120, inaccordance with certain example embodiments. The magnetic stripe card120 has a magnetic strip 505. The magnetic stripe 505 can storeinformation associated with the account of the user 101, such as theaccount number, the issuer, the expiration date, and other suitableinformation. The magnetic stripe 505 can transmit the information to amerchant system via a card reader or other suitable merchant point ofsale component capable of reading the information from the magneticstripe card 120. The magnetic stripe card 120 has a location for thesignature 535 of the user 101. The user 101 can sign the magnetic stripecard 120 for comparison with the signature of a user 101 at the time ofa purchase. The magnetic stripe card 120 has information 530 associatedwith the issuer of the magnetic stripe card 120, such as the phonenumber and a website. The magnetic stripe card 120 has a security code525 or other suitable code on the magnetic stripe card 120 for verifyingthe authenticity of the magnetic stripe card 120.

In the example, the account number 415, user name 410, and theexpiration date 420 are embossed on the front of the magnetic stripecard 120 and reverse of the embossed characters can be read on the backof the magnetic stripe card 120. The reversed characters will bedebossed on the back of the magnetic stripe card 120. That is, anycharacter that is embossed on the front of the magnetic stripe card 120will typically be debossed on the back of the magnetic stripe card 120.Thus, the account number 515 can be the reversed, debossed characters ofthe account number 415 from the front of the magnetic stripe card 120.The magnetic stripe card 120 displays the reversed name 510 of the user101. The magnetic stripe card 120 displays a reversed expiration date520 of the magnetic stripe card 120. In alternate examples, other datafrom the front of the magnetic stripe card 120 are embossed. In anotheralternate example, none of the data is embossed. The data can bereproduced on the back of the magnetic stripe card 120 in regular orreversed characters.

Example Processes

The example methods illustrated in FIG. 2-3 are described hereinafterwith respect to the components of the example operating environment 100.The example methods of FIG. 2-3 may also be performed with other systemsand in other environments.

FIG. 2 is a block flow diagram depicting a method 200 for method fordetecting card information from a reverse side image of a card, inaccordance with certain example embodiments.

With reference to FIGS. 1 and 2, in block 210, a card image processingmodule 115 on the user computing device 110 receives an image of theback of a magnetic stripe card 120. The user 101 employs a mobile phone,digital camera, or other user computing device 110 to capture an imageof the back of the magnetic stripe card 120 associated with the accountthat the user 101 desires to input into the mobile computing device. Forexample, a user 101 can capture an image of the magnetic stripe card 120with the camera on a user computing device 110 and access the image withthe card image processing module 115 on the user computing device 110.The image can alternatively be captured by a merchant system, paymentprocessing system 140, or any suitable party.

In block 220, the card image processing module 115 processes the imageto remove perspective distortion. For example, the image may not havebeen captured from the preferred angle, or the magnetic stripe card 120in the image may not fit the required frame for the image. The cardimage processing module 115 can alter or resize the image to fit anyrequired parameters for processing in the manner in which the card imageprocessing module 115 is configured to process images. In an example,the card image processing module 115 can detect the corners or edges ofthe magnetic stripe card 120 in the image and then map the corners oredges to a rectangle of the correct ratios for a credit card. The cardimage processing module 115 can perform any other required imageadjustments to provide a clear and useful image suitable for processingto obtain information included therein. The card image processing module115 can process the image through any automated image processingalgorithm stored on the card image processing module 115 or the cardimage processing module 115 can provide a user interface to allow theuser 101 to process the image manually.

In block 230, the card image processing module 115 detects the reversedembossed characters on the back of the magnetic stripe card 120. Forexample, the card image processing module 115 can detect the credit cardnumber, name, expiration date, and other embossed information from theback of magnetic stripe card 120. The detection can leverage knownspecifications for where characters are embossed within the space of themagnetic stripe card 120, by analyzing specific locations on themagnetic stripe card 120 for the corresponding information included ineach specific location. For example, the card image processing module115 can access a database, or other stored data, of credit cardinformation placement. The database can store the typical locations onthe card face of the typical data on a magnetic stripe card 120, such asthe card number and the expiration date. Additionally, the card imageprocessing module 115 can search the image of the magnetic stripe card120 for information that is not located in an expected location. Thecard image processing module 115 can employ character recognitionalgorithms or related techniques to identify a set of characters fromthe information identified on the magnetic stripe card 120.

Once embossed characters are located within the image of the back of themagnetic stripe card 120, they can be reversed, or mirrored, for normalrecognition. That is, as the embossed images on the back of the magneticstripe card 120 are reversed, the card image processing module 115 canprocess the characters to provide a mirror image of the characters toallow a character recognition algorithm to interpret the characters.After processing, the embossed set of characters appears “debossed” andreversed from the image. Alternatively, a reverse character recognitionalgorithm may be used that is capable of interpreting reversedcharacters.

In block 240, the card image processing module 115 can additionally oralternatively detect additional printed information from the back of themagnetic stripe card 120 that is not embossed or reversed. For example,the security code, signature, issuer name, address, and phone number,and other information of the issuing institution are generally notembossed and are generally located on the back of a magnetic stripe card120. The card image processing module 115 can read the printedinformation via any character recognition software stored on the cardimage processing module 115, or via any suitable method.

In block 250, after processing the information from the image to obtainan alpha-numeric character set for the information from the image, thecard image processing module 115 can verify uncertain detection withuser 101. For example, the user 101 may be queried to verify theprocessed information via a user interface provided by the card imageprocessing module 115 or the user computing device 110. The user 101 maybe prompted to verify the magnetic stripe card 120 information as adefault for some or all of the information. Alternatively, the user 101may only be required to verify information if the detection algorithmshave a low confidence in the accuracy of the processed information. Forexample, if the detection algorithms have a less than 90% certainty ofthe accuracy of the character set, then the card image processing module115 can provide the character set to the user 101 on a user interface ofthe card image processing module 115 and request a verification ormodification of the character set.

In block 260, the card image processing module 115 can provide thedetected card information for processing. The card image processingmodule 115 can categorize the information obtained from the magneticstripe card 120. For example, the card image processing module 115 candetermine that a set of characters from the magnetic stripe card 120relates to the account number, the user name, the expiration data, andother suitable information. The set of characters can be stored in thecard image processing module 115 with a designation associating theseries of characters with the appropriate category. For example, aseries of 16 numbers would be associated with an account identifier. Afour digit series with a “/” in the middle would be associated with anexpiration date.

The card image processing module 115 can provide detected magneticstripe card 120 information for further processing. In certainembodiments, the information may be communicated to a payment processingsystem 140 or other computing system to process a payment or otheroperation associated with the magnetic stripe card 120. For example, thecard image processing module 115 can communicate the card information toa digital wallet application module executing on the user computingdevice 110 or otherwise associated with the user 101 of the magneticstripe card 120 for use in a transaction with a merchant or otherentity. In another example, the user computing device 110 can use themagnetic stripe card 120 information to populate a payment form or otheronline transaction form to conduct a transaction. In another example, amerchant can use the magnetic stripe card 120 information to populate atransaction page on a point of sale terminal or other transaction userinterface. The magnetic stripe card 120 information can be employed forany other suitable purpose.

FIG. 3 is a block diagram depicting a method for detecting magneticstripe card 120 information by comparing results from front and reverseside image detection, in accordance with certain example embodiments.

In an example embodiment, correlation between images of the front andback of the magnetic stripe card 120 may help improve the accuracy ofreading the magnetic stripe card 120. An image of the front of themagnetic stripe card 120 may be harder to read because of backgroundimages, the embossing, and other information provided on the front ofthe magnetic stripe card 120. The back of the magnetic stripe card 120often overlaps with customer service information, the signature, orother images or information. Thus, errors may occur when extracting thecharacters and other user information from an image of the magneticstripe card 120.

Since both the front and the back of the magnetic stripe card 120contain some of the same information, such as the embossed information,the card image processing module 115 can compare information from thefront of the magnetic stripe card 120 with information from the back ofthe magnetic stripe card 120 and note similarities and differences.Information from the front of the magnetic stripe card 120 that matchesthe information from the back of the magnetic stripe card 120 can beexpected to be more accurate. If the information from the front of themagnetic stripe card 120 does not match the same information on the backof the magnetic stripe card 120, then the card image processing module115 may require user 101 input to select or input the correctinformation.

In block 310, a card image processing module 115 on the user computingdevice 110 receives the image of the front of the magnetic stripe card120. The user 101 employs a mobile phone, digital camera, or other usercomputing device 110 to capture an image of the back of the magneticstripe card 120 associated with the account that the user 101 desires toinput into the mobile computing device. For example, a user 101 cancapture an image of the magnetic stripe card 120 with the camera on auser computing device 110 and access the image with the card imageprocessing module 115 on the user computing device 110. The image canalternatively be captured by a merchant system, payment processingsystem 140, or any suitable party.

In block 320, a card image processing module 115 on the user computingdevice 110 receives the image of the back of the magnetic stripe card120. The user 101 employs a mobile phone, digital camera, or other usercomputing device 110 to capture an image of the back of the magneticstripe card 120 associated with the account that the user 101 desires toinput into the mobile computing device. For example, a user 101 cancapture an image of the magnetic stripe card 120 with the camera on auser computing device 110 and access the image with the card imageprocessing module 115 on the user computing device 110. The image canalternatively be captured by a merchant system, payment processingsystem 140, or any suitable party.

In block 330, the card image processing module 115 processes the imageof the front and the image of the back of the magnetic stripe card 120to remove perspective distortion. For example, the images may not havebeen captured from the preferred angle, or the magnetic stripe card 120in the images may not fit the required frame for the image. The cardimage processing module 115 can alter or resize the images to fit anyrequired parameters for processing in the manner in which the imageprocessing module is configured to process images. In an example, thecard image processing module 115 can detect the corners or edges of themagnetic stripe card 120 in one of the images and then map the cornersor edges to a rectangle of the correct ratios for a credit card. Thecard image processing module 115 can perform any other required imageadjustments to provide a clear and useful image suitable for processingto obtain information included therein. The card image processing module115 can process the images through any automated image processingalgorithm stored on the card image processing module 115 or the cardimage processing module 115 can provide a user interface to allow theuser 101 to process the images manually.

In block 340, the card image processing module 115 detects the embossedcharacters on the front of the magnetic stripe card 120. For example,the card image processing module 115 can detect the credit card number,name, expiration date, and other embossed information from the front ofmagnetic stripe card 120. The detection can leverage knownspecifications for where characters are embossed within the space of themagnetic stripe card 120, by analyzing specific locations on themagnetic stripe card 120 for the corresponding information included ineach specific location. For example, the card image processing module115 can access a database, or other stored data, of credit cardinformation placement. The database can store the typical locations onthe face of the typical data on a magnetic stripe card 120, such as thecard number and the expiration date. Additionally, the card imageprocessing module 115 can search the image of the magnetic stripe card120 for information that is not located in an expected location. Thecard image processing module 115 can employ character recognitionalgorithms or related techniques to identify a set of characters fromthe information identified on the magnetic stripe card 120.

Once embossed characters are located within the image of the front ofthe magnetic stripe card 120, the card image processing module 115 canprocess the characters to allow a character recognition algorithm tointerpret the characters. After processing, the embossed set ofcharacters appears “debossed” on the image. That is, the characters nolonger appear to be embossed and are more easily interpreted andrecognized.

In block 350, the card image processing module 115 detects the reversedembossed characters on the back of the magnetic stripe card 120. Forexample, the card image processing module 115 can detect the credit cardnumber, name, expiration date, and other embossed information from theback of magnetic stripe card 120. The detection can leverage knownspecifications for where characters are embossed within the space of themagnetic stripe card 120, by analyzes specific locations on the magneticstripe card 120 for the corresponding information included in eachspecific location. For example, the card image processing module 115 canaccess a database, or other stored data, of credit card informationplacement. The database can store the typical locations on the face ofthe typical data on a magnetic stripe card 120, such as the card numberand the expiration date. Additionally, the card image processing module115 can search the image of the magnetic stripe card 120 for informationthat is not located in an expected location. The card image processingmodule 115 can employ character recognition algorithms or relatedtechniques to identify a set of characters from the informationidentified on the magnetic stripe card 120.

Once embossed characters are located within the image of the back of themagnetic stripe card 120, they can be reversed, or mirrored, for normalrecognition. That is, as the embossed images on the back of the magneticstripe card 120 are reversed, the card image processing module 115 canprocess the characters to provide a mirror image of the characters toallow a character recognition algorithm to interpret the characters.After processing, the embossed set of characters appears “debossed” andreversed from the image.

In block 360, the card image processing module 115 can additionally oralternatively detect additional printed information from the back of themagnetic stripe card 120 that is not embossed or reversed. For example,the security code, signature, issuer name, address, and phone number,and other information of the issuing institution are generally notembossed and are generally located on the back of a magnetic stripe card120. The card image processing module 115 can read the printedinformation via any character recognition software stored on the cardimage processing module 115, or via any suitable method.

In block 370, the card image processing module 115 can compare detectedinformation from the front and back of the magnetic stripe card 120.Correlation between images of the front and back of the magnetic stripecard 120 may help improve the accuracy of reading the magnetic stripecard 120. After determining the category of each series of charactersfrom the images of the front and back of the magnetic stripe card 120,the card image processing module 115 can compare the information fromthe front of the magnetic stripe card 120 with the information from theback of the magnetic stripe card 120.

For example, the card image processing module 115 can compare a seriesof characters from the back associated with the user 101 name to theseries of characters from the front associated with the user 101 name.The card image processing module 115 can use the comparison to determinea confidence score for the accuracy of the user 101 name. If thecomparison produces an exact match, then the confidence score for theuser 101 name would be high. If a conflict exists between the two, thenthe confidence score for the user 101 name would be lower. The relativeconfidence score can depend on a number of conflicts between theinformation from the front and back sides of the magnetic stripe card120. If the confidence score is below a configurable threshold, the cardimage processing module 115 may request an input from the user 101 toverify the correct information. For example, the card image processingmodule 115 may provide the results extracted from the front of themagnetic stripe card 120 and the results extracted from the back of themagnetic stripe card 120 and allow the user 101 to select the correctinformation or input alternate information.

In an example embodiment, the card image processing module 115 can applyindependent character recognition applications to the characters on thefront and back of the magnetic stripe card 120. For example, the cardimage processing module 115 can host two or more character recognitionapplications and apply one character recognition application to thefront of the magnetic stripe card 120 and a different characterrecognition application to the back of the magnetic stripe card 120.After determining the category of each series of characters, the cardimage processing module 115 can compare the information from the frontof the magnetic stripe card 120 with the information from the back ofthe magnetic stripe card 120 to improve the accuracy of the information.The agreement of different character recognizer processing applicationson the characters on the front and back of the magnetic stripe card 120can provide a greater degree of confidence in the extracted information.

In another example embodiment, the card image processing module 115 canextract features from corresponding locations on the front and back ofthe magnetic stripe card 120, and feed the combined features into asingle classifier. The card image processing module 115 can extract theembossed characters from the same area of the magnetic stripe card 120on the front and the back. For example, the card image processing module115 can extract the account number from the front of the magnetic stripecard 120 and combine the characters with the characters extracted fromthe same, although reversed, location on the back of the magnetic stripecard 120.

The card image processing module 115 can reverse one of the sets ofcharacters and process the two sets of characters together to achieve amore accurate set of characters. The card image processing module 115can apply a character recognition application to the characters toidentify the set of characters and categorize the information.

In another example embodiment, the card image processing module 115 cansearch for and identify correlations between pixels on the front andback of the magnetic stripe card 120, and extract pixels for which thereare strong correlations. The card image processing module 115 canprocess digital images of the front and back of the magnetic stripe card120 and compare the individual pixels searching for correlations anddifferences. The pixels with high correlations are likely to becorresponding parts of characters rather than of the backgrounds. Thecorrelated pixels can allow a greater level of accuracy when identifyingand recognizing characters.

In another example embodiment, the card image processing module 115 canuse more than one source to extract additional information. The cardimage processing module 115 can process multiple images of the front,the back, or both. For example, the user 101 can provide multiple imagescaptured from different angles to allow the card image processing module115 to better filter shadows, scratches, or other obstructions.Additionally or alternatively, the user 101 can provide a video movingacross the magnetic stripe card 120 such that many angles can providemore information to the card image processing module 115 for processing.

In block 380, after processing the information from the images to obtainan alpha-numeric character set for the information from the images, thecard image processing module 115 can verify uncertain detection withuser 101. For example, the user 101 may be queried to verify theprocessed information via a user interface provided by the card imageprocessing module 115 or the user computing device 110. The user 101 maybe prompted to verify the card information as a default for some or allof the information. Alternatively, the user 101 may only be required toverify information if the detection algorithms have a low confidence inthe accuracy of the processed information. For example, if the detectionalgorithms have a less than 90% certainty of the accuracy of thecharacter set, then the card image processing module 115 can provide thecharacter set to the user 101 on a user interface of the card imageprocessing module 115 and request a verification or modification of thecharacter set.

In block 390, the card image processing module 115 can provide thedetected magnetic stripe card 120 information for processing. The cardimage processing module 115 can categorize the information obtained fromthe magnetic stripe card 120. For example, the card image processingmodule 115 can determine that a set of characters from the magneticstripe card 120 relates to the account number, the user 101 name, theexpiration data, and other suitable information. The set of characterscan be stored in the card image processing module 115 with a designationassociating the series of characters with the appropriate category. Forexample, a series of 16 numbers would be associated with an accountidentifier. A four digit series with a “/” in the middle would beassociated with an expiration date.

The card image processing module 115 can provide detected magneticstripe card 120 information for further processing. In certainembodiments, the information may be communicated to a payment processingsystem 140 or other computing system to process a payment or otheroperation associated with the magnetic stripe card 120. For example, thecard image processing module 115 can communicate the magnetic stripecard 120 information to a digital wallet application module executing onthe user computing device 110 or otherwise associated with the user 101of the magnetic stripe card 120 for use in a transaction with a merchantor other entity. In another example, the user computing device 110 canuse the magnetic stripe card 120 information to populate a payment formor other online transaction form to conduct a transaction. In anotherexample, a merchant can use the magnetic stripe card 120 information topopulate a transaction page on a point of sale terminal or othertransaction user interface. The magnetic stripe card 120 information canbe employed for any other suitable purpose.

Although described herein as executing on the user computing device 110,the card image processing module 115 can execute on any suitablecomputing device. For example, the card image processing module 115 canexecute on a payment processing system 140, a merchant point of salesystem, a digital wallet account management system, or other suitablecomputing system. In these embodiments, the captured images of the frontand back of the magnetic stripe card 120 are communicated from the imagecapture device to the processing computing system for processing of theimage information.

Example Systems

FIG. 6 depicts a computing machine 2000 and a module 2050 in accordancewith certain example embodiments. The computing machine 2000 maycorrespond to any of the various computers, servers, mobile devices,embedded systems, or computing systems presented herein. The module 2050may comprise one or more hardware or software elements configured tofacilitate the computing machine 2000 in performing the various methodsand processing functions presented herein. The computing machine 2000may include various internal or attached components such as a processor2010, system bus 2020, system memory 2030, storage media 2040,input/output interface 2060, and a network interface 2070 forcommunicating with a network 2080.

The computing machine 2000 may be implemented as a conventional computersystem, an embedded controller, a laptop, a server, a mobile device, asmartphone, a set-top box, a kiosk, a vehicular information system, onemore processors associated with a television, a customized machine, anyother hardware platform, or any combination or multiplicity thereof. Thecomputing machine 2000 may be a distributed system configured tofunction using multiple computing machines interconnected via a datanetwork or bus system.

The processor 2010 may be configured to execute code or instructions toperform the operations and functionality described herein, managerequest flow and address mappings, and to perform calculations andgenerate commands. The processor 2010 may be configured to monitor andcontrol the operation of the components in the computing machine 2000.The processor 2010 may be a general purpose processor, a processor core,a multiprocessor, a reconfigurable processor, a microcontroller, adigital signal processor (“DSP”), an application specific integratedcircuit (“ASIC”), a graphics processing unit (“GPU”), a fieldprogrammable gate array (“FPGA”), a programmable logic device (“PLD”), acontroller, a state machine, gated logic, discrete hardware components,any other processing unit, or any combination or multiplicity thereof.The processor 2010 may be a single processing unit, multiple processingunits, a single processing core, multiple processing cores, specialpurpose processing cores, co-processors, or any combination thereof.According to certain embodiments, the processor 2010 along with othercomponents of the computing machine 2000 may be a virtualized computingmachine executing within one or more other computing machines.

The system memory 2030 may include non-volatile memories such asread-only memory (“ROM”), programmable read-only memory (“PROM”),erasable programmable read-only memory (“EPROM”), flash memory, or anyother device capable of storing program instructions or data with orwithout applied power. The system memory 2030 may also include volatilememories such as random access memory (“RAM”), static random accessmemory (“SRAM”), dynamic random access memory (“DRAM”), synchronousdynamic random access memory (“SDRAM”). Other types of RAM also may beused to implement the system memory 2030. The system memory 2030 may beimplemented using a single memory module or multiple memory modules.While the system memory 2030 is depicted as being part of the computingmachine 2000, one skilled in the art will recognize that the systemmemory 2030 may be separate from the computing machine 2000 withoutdeparting from the scope of the subject technology. It should also beappreciated that the system memory 2030 may include, or operate inconjunction with, a non-volatile storage device such as the storagemedia 2040.

The storage media 2040 may include a hard disk, a floppy disk, a compactdisc read only memory (“CD-ROM”), a digital versatile disc (“DVD”), aBlu-ray disc, a magnetic tape, a flash memory, other non-volatile memorydevice, a solid sate drive (“SSD”), any magnetic storage device, anyoptical storage device, any electrical storage device, any semiconductorstorage device, any physical-based storage device, any other datastorage device, or any combination or multiplicity thereof. The storagemedia 2040 may store one or more operating systems, application programsand program modules such as module 2050, data, or any other information.The storage media 2040 may be part of, or connected to, the computingmachine 2000. The storage media 2040 may also be part of one or moreother computing machines that are in communication with the computingmachine 2000 such as servers, database servers, cloud storage, networkattached storage, and so forth.

The module 2050 may comprise one or more hardware or software elementsconfigured to facilitate the computing machine 2000 with performing thevarious methods and processing functions presented herein. The module2050 may include one or more sequences of instructions stored assoftware or firmware in association with the system memory 2030, thestorage media 2040, or both. The storage media 2040 may thereforerepresent examples of machine or computer readable media on whichinstructions or code may be stored for execution by the processor 2010.Machine or computer readable media may generally refer to any medium ormedia used to provide instructions to the processor 2010. Such machineor computer readable media associated with the module 2050 may comprisea computer software product. It should be appreciated that a computersoftware product comprising the module 2050 may also be associated withone or more processes or methods for delivering the module 2050 to thecomputing machine 2000 via the network 2080, any signal-bearing medium,or any other communication or delivery technology. The module 2050 mayalso comprise hardware circuits or information for configuring hardwarecircuits such as microcode or configuration information for an FPGA orother PLD.

The input/output (“I/O”) interface 2060 may be configured to couple toone or more external devices, to receive data from the one or moreexternal devices, and to send data to the one or more external devices.Such external devices along with the various internal devices may alsobe known as peripheral devices. The I/O interface 2060 may include bothelectrical and physical connections for operably coupling the variousperipheral devices to the computing machine 2000 or the processor 2010.The I/O interface 2060 may be configured to communicate data, addresses,and control signals between the peripheral devices, the computingmachine 2000, or the processor 2010. The I/O interface 2060 may beconfigured to implement any standard interface, such as small computersystem interface (“SCSI”), serial-attached SCSI (“SAS”), fiber channel,peripheral component interconnect (“PCI”), PCI express (PCIe), serialbus, parallel bus, advanced technology attached (“ATA”), serial ATA(“SATA”), universal serial bus (“USB”), Thunderbolt, FireWire, variousvideo buses, and the like. The I/O interface 2060 may be configured toimplement only one interface or bus technology. Alternatively, the I/Ointerface 2060 may be configured to implement multiple interfaces or bustechnologies. The I/O interface 2060 may be configured as part of, allof, or to operate in conjunction with, the system bus 2020. The I/Ointerface 2060 may include one or more buffers for bufferingtransmissions between one or more external devices, internal devices,the computing machine 2000, or the processor 2010.

The I/O interface 2060 may couple the computing machine 2000 to variousinput devices including mice, touch-screens, scanners, biometricreaders, electronic digitizers, sensors, receivers, touchpads,trackballs, cameras, microphones, keyboards, any other pointing devices,or any combinations thereof. The I/O interface 2060 may couple thecomputing machine 2000 to various output devices including videodisplays, speakers, printers, projectors, tactile feedback devices,automation control, robotic components, actuators, motors, fans,solenoids, valves, pumps, transmitters, signal emitters, lights, and soforth.

The computing machine 2000 may operate in a networked environment usinglogical connections through the network interface 2070 to one or moreother systems or computing machines across the network 2080. The network2080 may include wide area networks (WAN), local area networks (LAN),intranets, the Internet, wireless access networks, wired networks,mobile networks, telephone networks, optical networks, or combinationsthereof. The network 2080 may be packet switched, circuit switched, ofany topology, and may use any communication protocol. Communicationlinks within the network 2080 may involve various digital or an analogcommunication media such as fiber optic cables, free-space optics,waveguides, electrical conductors, wireless links, antennas,radio-frequency communications, and so forth.

The processor 2010 may be connected to the other elements of thecomputing machine 2000 or the various peripherals discussed hereinthrough the system bus 2020. It should be appreciated that the systembus 2020 may be within the processor 2010, outside the processor 2010,or both. According to some embodiments, any of the processor 2010, theother elements of the computing machine 2000, or the various peripheralsdiscussed herein may be integrated into a single device such as a systemon chip (“SOC”), system on package (“SOP”), or ASIC device.

In situations in which the systems discussed here collect personalinformation about users, or may make use of personal information, theusers may be provided with a opportunity to control whether programs orfeatures collect user information (e.g., information about a user'ssocial network, social actions or activities, profession, a user'spreferences, or a user's current location), or to control whether and/orhow to receive content from the content server that may be more relevantto the user. In addition, certain data may be treated in one or moreways before it is stored or used, so that personally identifiableinformation is removed. For example, a user's identity may be treated sothat no personally identifiable information can be determined for theuser, or a user's geographic location may be generalized where locationinformation is obtained (such as to a city, ZIP code, or state level),so that a particular location of a user cannot be determined. Thus, theuser may have control over how information is collected about the userand used by a content server.

Embodiments may comprise a computer program that embodies the functionsdescribed and illustrated herein, wherein the computer program isimplemented in a computer system that comprises instructions stored in amachine-readable medium and a processor that executes the instructions.However, it should be apparent that there could be many different waysof implementing embodiments in computer programming, and the embodimentsshould not be construed as limited to any one set of computer programinstructions. Further, a skilled programmer would be able to write sucha computer program to implement an embodiment of the disclosedembodiments based on the appended flow charts and associated descriptionin the application text. Therefore, disclosure of a particular set ofprogram code instructions is not considered necessary for an adequateunderstanding of how to make and use embodiments. Further, those skilledin the art will appreciate that one or more aspects of embodimentsdescribed herein may be performed by hardware, software, or acombination thereof, as may be embodied in one or more computingsystems. Moreover, any reference to an act being performed by a computershould not be construed as being performed by a single computer as morethan one computer may perform the act.

The example embodiments described herein can be used with computerhardware and software that perform the methods and processing functionsdescribed previously. The systems, methods, and procedures describedherein can be embodied in a programmable computer, computer-executablesoftware, or digital circuitry. The software can be stored oncomputer-readable media. For example, computer-readable media caninclude a floppy disk, RAM, ROM, hard disk, removable media, flashmemory, memory stick, optical media, magneto-optical media, CD-ROM, etc.Digital circuitry can include integrated circuits, gate arrays, buildingblock logic, field programmable gate arrays (FPGA), etc.

The example systems, methods, and acts described in the embodimentspresented previously are illustrative, and, in alternative embodiments,certain acts can be performed in a different order, in parallel with oneanother, omitted entirely, and/or combined between different exampleembodiments, and/or certain additional acts can be performed, withoutdeparting from the scope and spirit of various embodiments. Accordingly,such alternative embodiments are included in the inventions claimedherein.

Although specific embodiments have been described above in detail, thedescription is merely for purposes of illustration. It should beappreciated, therefore, that many aspects described above are notintended as required or essential elements unless explicitly statedotherwise. Modifications of, and equivalent components or actscorresponding to, the disclosed aspects of the example embodiments, inaddition to those described above, can be made by a person of ordinaryskill in the art, having the benefit of the present disclosure, withoutdeparting from the spirit and scope of embodiments defined in thefollowing claims, the scope of which is to be accorded the broadestinterpretation so as to encompass such modifications and equivalentstructures.

What is claimed is:
 1. A computer-implemented method for capturinginformation from payment instruments, comprising: receiving, using oneor more computing devices, an image of a back side of a payment card,the payment card comprising information imprinted thereon such that theimprinted information protrudes from a front side of the payment cardand the imprinted information is indented into the back side of thepayment instrument; extracting, using the one or more computing devices,sets of characters from the image of the back side of the payment cardbased on the imprinted information indented into the back side of thepayment card and depicted in the image of the back side of the paymentcard; applying, using the one or more computing devices, a firstcharacter recognition application to process the sets of charactersextracted from the image of the back side of the payment card; andcategorizing, using the one or more computing devices, each of the setsof characters into one of a plurality of categories relating toinformation required to conduct a payment transaction.
 2. Thecomputer-implemented method of claim 1, further comprisingcommunicating, using the one or more computing devices, the sets ofcharacters and the categories associated with the sets of characters toa digital wallet application module for use in a payment transaction. 3.The computer-implemented method of claim 1, further comprisingreversing, using the one or more computing devices, the imprintedinformation from the back side of the payment card in connection withapplying the first character recognition application.
 4. Thecomputer-implemented method of claim 1, further comprising: receiving,using the one or more computing devices, an image of a front side of thepayment card; extracting, using the one or more computing devices, setsof characters from the image of the front side of the payment card basedon the imprinted information protruding from the front side of thepayment card and depicted in the image of the front side of the paymentcard; applying, using the one or more computing devices, a secondcharacter recognition application to process the sets of charactersextracted from the image of the front side of the payment card;categorizing, using the one or more computing devices, each of the setsof characters into one of the plurality of categories relating toinformation required to conduct a payment transaction; comparing, usingthe one or more computing devices, a processed set of characters fromthe front side of the payment card associated with a particular one ofthe categories to a processed set of characters from the back side ofthe payment card associated with the particular one of the categories;and refining, using the one or more computing devices, the processing ofthe compared sets of characters from the front side and the back side ofthe payment card based on the comparison of the compared sets ofcharacters from the front side and the back side of the payment card. 5.The computer-implemented method of claim 4, further comprising:displaying, using the one or more computing devices, a request for avalidation or correction of at least one of the sets of characters, inresponse to the comparison determining that the processed set ofcharacters from the front side of the payment card associated with theparticular one of the categories differ from the processed set ofcharacters from the back side of the payment card associated with theparticular one of the categories.
 6. The computer-implemented method ofclaim 4, wherein the first and second character recognition applicationsare a same application.
 7. The computer-implemented method of claim 4,wherein the first and second character recognition applications aredifferent.
 8. The computer-implemented method of claim 1, furthercomprising: receiving, using the one or more computing devices, an imageof the front side of the payment card; determining, using the one ormore computing devices, a first set of characters from the front of thepayment card that are in a location on the payment card that correspondsto a second set of characters on the back side of the payment card; andcombining, using the one or more computing devices, the images of thefirst set of characters and the second set of characters to produce acombined set of characters, wherein the first character recognitionprocess is applied to the combined set of characters.
 9. Thecomputer-implemented method of claim 1, wherein the image of back sideof the payment card is captured by a camera operating on the one or morecomputing devices.
 10. The computer-implemented method of claim 1,wherein the categories comprise one or more of a user account number, auser name, an account expiration date, a phone number of an issuer ofthe account, and a signature of the user.
 11. The computer-implementedmethod of claim 1, wherein the payment card comprises a credit card, adebit card, a stored value card, or a loyalty card.
 12. A computerprogram product, comprising: a non-transitory computer-readable storagedevice having computer-executable program instructions embodied thereonthat when executed by a computer cause the computer to select paymentinstruments for proxy card transactions, the computer-executable programinstructions comprising: computer-executable program instructions toreceive an image of a back side of a payment instrument, the paymentinstrument comprising information imprinted thereon such that theimprinted information protrudes from a front side of the paymentinstrument and the imprinted information is indented into the back sideof the payment instrument; computer-executable program instructions toextract sets of characters from the image of the back side of thepayment instrument based on the imprinted information indented into theback side of the payment instrument and depicted in the image of theback side of the payment instrument; computer-executable programinstructions to apply a first character recognition application toprocess the sets of characters extracted from the image of the back sideof the payment instrument; and computer-executable program instructionsto categorize each of the sets of characters into one of a plurality ofcategories relating to information required to conduct a paymenttransaction.
 13. The computer program product of claim 12, furthercomprising computer-executable program instructions to communicate thesets of characters and the categories associated with the sets ofcharacters to a digital wallet application module for use in a paymenttransaction.
 14. The computer program product of claim 12, furthercomprising computer-executable program instructions to receive theimprinted information from the back side of the payment instrument inconnection with applying the first character recognition application.15. The computer program product of claim 12, further comprising:computer-executable program instructions to receive an image of a frontside of the payment instrument; computer-executable program instructionsto extract sets of characters from the image of the front side of thepayment instrument based on the imprinted information protruding fromthe front side of the payment instrument and depicted in the image ofthe front side of the payment instrument; computer-executable programinstructions to apply a second character recognition application toprocess the sets of characters extracted from the image of the frontside of the payment instrument; computer-executable program instructionsto categorize each of the sets of characters into one of the pluralityof categories relating to information required to conduct a paymenttransaction; computer-executable program instructions to compare aprocessed set of characters from the front side of the paymentinstrument associated with a particular one of the categories to aprocessed set of characters from the back side of the payment instrumentassociated with the particular one of the categories; andcomputer-executable program instructions to refine the processing of thecompared sets of characters from the front side and the back side of thepayment instrument based on the comparison of the compared sets ofcharacters from the front side and the back side of the paymentinstrument.
 16. A system to select payment instruments for proxy cardtransactions, the system comprising: a storage resource; and a processorcommunicatively coupled to the storage resource, wherein the processorexecutes application code instructions that are stored in the storageresource and that cause the system to: receive an image of a back sideof a payment instrument, the payment instrument comprising informationimprinted thereon such that the imprinted information protrudes from afront side of the payment instrument and the imprinted information isindented into the back side of the payment instrument; extract sets ofcharacters from the image of the back side of the payment instrumentbased on the imprinted information indented into the back side of thepayment instrument and depicted in the image of the back side of thepayment instrument; apply a first character recognition application toprocess the sets of characters extracted from the image of the back sideof the payment instrument; and categorize each of the sets of charactersinto one of a plurality of categories relating to information requiredto conduct a payment transaction.
 17. The system of claim 16, theprocessor executing further application code instructions that arestored in the storage resource and that cause the system to: receive animage of a front side of the payment instrument; extract sets ofcharacters from the image of the front side of the payment instrumentbased on the imprinted information protruding from the front side of thepayment instrument and depicted in the image of the front side of thepayment instrument; apply a second character recognition application toprocess the sets of characters extracted from the image of the frontside of the payment instrument; categorize each of the sets ofcharacters into one of the plurality of categories relating toinformation required to conduct a payment transaction; compare aprocessed set of characters from the front side of the paymentinstrument associated with a particular one of the categories to aprocessed set of characters from the back side of the payment instrumentassociated with the particular one of the categories; and refine theprocessing of the compared sets of characters from the front side andthe back side of the payment instrument based on the comparison of thecompared sets of characters from the front side and the back side of thepayment instrument.
 18. The system of claim 17, the processor executingfurther application code instructions that are stored in the storageresource and that cause the system to display a request for a validationor correction of at least one of the sets of characters, in response tothe comparison determining that the processed set of characters from thefront side of the payment instrument associated with the particular oneof the categories differ from the processed set of characters from theback side of the payment instrument associated with the particular oneof the categories.
 19. The system of claim 17, wherein the first andsecond character recognition applications are a same application. 20.The system of claim 17, the processor executing further application codeinstructions that are stored in the storage resource and that cause thesystem to: receive an image of the front side of the payment instrument;determine a first set of characters from the front of the paymentinstrument that are in a location on the payment instrument thatcorresponds to a second set of characters on the back side of thepayment instrument; and combine the first set of characters and thesecond set of characters to produce an image of a combined set ofcharacters, wherein the first character recognition process is appliedto the combined set of characters.